A Tensor Based Unified Framework for Streaming Signal Online Analysis

被引：0
|
作者：
Ma, Baoze [1 ]
Wang, Xin [2 ]
Wen, Ce [2 ]
Yi, Chen [2 ]
Yang, Yuanyikai [1 ]
机构：
[1] Chongqing Univ Posts & Telecommun, Sch Optoelect Engn, Chongqing 400065, Peoples R China
[2] Chongqing Univ Posts & Telecommun, Sch Commun & Informat Engn, Chongqing 400065, Peoples R China
来源：
IEEE SIGNAL PROCESSING LETTERS | 2024年 / 31卷
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Tensors; Vectors; Matrix decomposition; Streams; Kernel; Real-time systems; Linear programming; Online optimization; tensor tracking; streaming signal analysis; low-rank tensor approximation; COMPLETION;
D O I：
10.1109/LSP.2024.3413302
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
To explore the online tensor analysis technique in single-aspect streaming model, a tensor based unified framework encompassed more tensor formats than one is proposed according to the structure of the last tensor factor. We found that the temporal slice only changes the size of factor matrix corresponding to the temporal dimension in unified framework. Consequently, the block-coordinate descent strategy is utilized to calculate the temporal tensor factor and non-temporal decomposition components respectively based on exponentially weighted cost function. The simulation results indicate that the presented unified framework provides a superior reconstruction performance compared to the existing tensor tracking methods in real video scenarios.
引用
收藏
页码：2445 / 2449
页数：5
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